Quality Control, Antidiabetic, and Anti-inflammatory Effects, as Measured by Alpha-Amylase and Alpha-Glucosidase Activities, of a Weight-Loss Remedy from Worayokasan Scripture
Bibliographic record
Abstract
Introduction: Diabetes increases the risk of free radical generation and health complications. Obesity is a major risk factor for Type 2 Diabetes (T2DM). The Weight-Loss (WL) remedy from Worayokasan scripture, consisting of Cyperus rotundus L. (CR), Terminalia chebula Retz. (TCb), and Tinospora crispa (L.) Miers ex Hook.f. & Thomson (TCp). The WL remedy is used to reduce obesity, nourish the body, and act as atonic. However, there is currently limited information on this natural remedy's potential anti-diabetic and anti-inflammatory effects. Objectives: The objectives of this study were to evaluate the anti-diabetic, and anti-inflammatory properties and quality control of the WL remedy and its plant ingredients. Methods: The quality control was conducted using the Thai Herbal Pharmacopoeia (THP) method. The potential anti-diabetic effects were evaluated through the inhibition of α-amylase and α-glucosidase enzymes, and the potential anti-inflammatory effects were measured by assessing the reduction of nitric oxide (NO) production in the WL remedy and its plant constituents. Results: The WL remedy passed the quality control guidelines set by the THP. TCpW demonstrated the most potent α-amylase inhibitory activity, with IC50 of 201.28 µg/mL, surpassing acarbose. WLH, WLW, and WLE showed moderate α-glucosidase inhibitory activity. However, all samples exhibitory low α-amylase inhibitory activity. The CRE extract exhibited the strongest anti-inflammatory activity by inhibiting NO production with an IC50 value of 31.93 µg/mL. Conclusions: The results suggest that the WL remedy possessed anti-diabetic and weight-loss characteristics, and has the potential to be developed into a dietary supplement for individuals with T2DM.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".